post-training-quantization

There are 31 repositories under post-training-quantization topic.

  • 666DZY666/micronet

    micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

    Language:Python2.2k40109477

  • intel/neural-compressor

    SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime

    Language:Python2k34186245

  • alibaba/TinyNeuralNetwork

    TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.

    Language:Python71821131118

  • SqueezeAILab/SqueezeLLM

    [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization

    Language:Python588172437

  • megvii-research/Sparsebit

    A model compression and acceleration toolbox based on pytorch.

    Language:Python321123039

  • megvii-research/FQ-ViT

    [IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer

    Language:Python28854446

  • Xiuyu-Li/q-diffusion

    [ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.

    Language:Python276173620

  • sayakpaul/Adventures-in-TensorFlow-Lite

    This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.

    Language:Jupyter Notebook16812633

  • ModelTC/llmc

    This is the official PyTorch implementation of "LLM-QBench: A Benchmark Towards the Best Practice for Post-training Quantization of Large Language Models", and also an efficient LLM compression tool with various advanced compression methods, supporting multiple inference backends.

    Language:Python104838

  • hkproj/quantization-notes

    Notes on quantization in neural networks

    Language:Jupyter Notebook382110

  • Sanjana7395/static_quantization

    Post-training static quantization using ResNet18 architecture

    Language:Jupyter Notebook36017

  • ModelTC/TFMQ-DM

    [CVPR 2024 Highlight] This is the official PyTorch implementation of "TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models".

    Language:Jupyter Notebook291003

  • ModelTC/QLLM

    [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models"

    Language:Python2580

  • zysxmu/FDDA

    Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization

    Language:Python14101

  • KwangHoonAn/Quantizations

    Language:Python13204

  • iszry/DI2N-PTQ4DM

    Improved the performance of 8-bit PTQ4DM expecially on FID.

    Language:Python9100

  • likholat/openvino_quantization

    This sample shows how to convert TensorFlow model to OpenVINO IR model and how to quantize OpenVINO model.

    Language:Python5350

  • Rumeysakeskin/ASR-Quantization

    Post-training quantization on Nvidia Nemo ASR model

    Language:Jupyter Notebook510

  • ssi-research/eptq

    Implementation of EPTQ - an Enhanced Post-Training Quantization algorithm for DNN compression

    Language:Python4200

  • yester31/Quantization_EX

    quantization example for pqt & qat

    Language:Python4102

  • yester31/TensorRT_ONNX

    Generating tensorrt model using onnx

    Language:C++3101

  • AndreiZoltan/ptq_resnet20

    Low-bit (2/4/8/16) Post Training Quantization for ResNet20

    Language:Python2100

  • generalMG/Medical-Dataset-Deep-Learning-Quantization-Data-Analysis

    The repository discusses a research work published on MDPI Sensors and provides details about the project.

    Language:Python2100

  • satya15july/quantization

    Model Quantization with Pytorch, Tensorflow & Larq

    Language:C++2201

  • smpanaro/norm-tweaking

    Post post-training-quantization (PTQ) method for improving LLMs. Unofficial implementation of https://arxiv.org/abs/2309.02784

    Language:Python2300

  • yashmaniya0/Quantization-of-Image-Classification-Models

    Comprehensive study on the quantization of various CNN models, employing techniques such as Post-Training Quantization and Quantization Aware Training (QAT).

    Language:Jupyter Notebook2100

  • OmidGhadami95/EfficientNetV2_Quantization_CK

    EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.

    Language:Jupyter Notebook1100

  • TanyaChutani/Quantization_Tensorflow

    Quantization for Object Detection in Tensorflow 2.x

    Language:Python120

  • andrea-zanette/HippoScan

    A framework to train a ResUNet architecture, quantize, compile and execute it on an FPGA.

    Language:Jupyter Notebook0200

  • amikom-gace-research-group/characterize-ptq-tensorrt

    Research experiments archive for post-training quantization with TensorRT. Submitted and Accepted to IEEE EDGE 2024

    Language:Python

  • raj2022/quantization_prunings

    Post-Training quantization perfomed on the model trained with CLIC dataset.

    Language:Jupyter Notebook10